Development of issue sets from social big data: A case study of green energy and low-carbon

Chun Che Huang; Yu Jie Fang; Shian Hua Lin; Wen Yau Liang; Shu Rong Wu

doi:10.1007/978-3-319-41561-1_11

Development of issue sets from social big data: A case study of green energy and low-carbon

Chun Che Huang, Yu Jie Fang, Shian Hua Lin, Wen Yau Liang, Shu Rong Wu

Department of Information Management

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

“Energy” has been one element of the development of human civilization, also a power for national industry, construction and economic development. The green energy has become the cornerstone in sustainable development to secure such energy supply but may accommodate opinions from controversial perspectives when this subject is discussed. This study develops an interactive big data system, which aims at aggregating data from Facebook, PTT, news, and provides an interactive interface for energy domain experts. The “interaction” characterizes the seamless integration between users and the system to construct the controversial issue sets of energy, which could be identified and established autonomously in this study. The approach using tags of the link in two controversial issues can help end-users effectively query on demand. The energy relevant issues can be fully aware and provided to the decision makers from the positive and negative viewpoints.

Original language	English
Title of host publication	Advances in Data Mining
Subtitle of host publication	Applications and Theoretical Aspects - 16th Industrial Conference, ICDM 2016, Proceedings
Editors	Petra Perner
Publisher	Springer Verlag
Pages	139-153
Number of pages	15
ISBN (Print)	9783319415604
DOIs	https://doi.org/10.1007/978-3-319-41561-1_11
Publication status	Published - 2016 Jan 1
Event	16th Industrial Conference on Advances in Data Mining, ICDM 2016 - New York, United States Duration: 2016 Jul 13 → 2016 Jul 17

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9728
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	16th Industrial Conference on Advances in Data Mining, ICDM 2016
Country	United States
City	New York
Period	16-07-13 → 16-07-17

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All Science Journal Classification (ASJC) codes

Theoretical Computer Science
Computer Science(all)

Cite this

Huang, C. C., Fang, Y. J., Lin, S. H., Liang, W. Y., & Wu, S. R. (2016). Development of issue sets from social big data: A case study of green energy and low-carbon. In P. Perner (Ed.), Advances in Data Mining: Applications and Theoretical Aspects - 16th Industrial Conference, ICDM 2016, Proceedings (pp. 139-153). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9728). Springer Verlag. https://doi.org/10.1007/978-3-319-41561-1_11

Huang, Chun Che ; Fang, Yu Jie ; Lin, Shian Hua ; Liang, Wen Yau ; Wu, Shu Rong. / Development of issue sets from social big data : A case study of green energy and low-carbon. Advances in Data Mining: Applications and Theoretical Aspects - 16th Industrial Conference, ICDM 2016, Proceedings. editor / Petra Perner. Springer Verlag, 2016. pp. 139-153 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Huang, CC, Fang, YJ, Lin, SH, Liang, WY & Wu, SR 2016, Development of issue sets from social big data: A case study of green energy and low-carbon. in P Perner (ed.), Advances in Data Mining: Applications and Theoretical Aspects - 16th Industrial Conference, ICDM 2016, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9728, Springer Verlag, pp. 139-153, 16th Industrial Conference on Advances in Data Mining, ICDM 2016, New York, United States, 16-07-13. https://doi.org/10.1007/978-3-319-41561-1_11

Development of issue sets from social big data : A case study of green energy and low-carbon. / Huang, Chun Che; Fang, Yu Jie; Lin, Shian Hua; Liang, Wen Yau; Wu, Shu Rong.

Advances in Data Mining: Applications and Theoretical Aspects - 16th Industrial Conference, ICDM 2016, Proceedings. ed. / Petra Perner. Springer Verlag, 2016. p. 139-153 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9728).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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Huang CC, Fang YJ, Lin SH, Liang WY, Wu SR. Development of issue sets from social big data: A case study of green energy and low-carbon. In Perner P, editor, Advances in Data Mining: Applications and Theoretical Aspects - 16th Industrial Conference, ICDM 2016, Proceedings. Springer Verlag. 2016. p. 139-153. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-41561-1_11

Access to Document

10.1007/978-3-319-41561-1_11